Innovative technologies like Artificial Intelligence (AI) and Machine Learning
are essential enablers of digital transformation. The unique ability to distill all complex data into knowledge, along with judgment (AI) and mechanical rules (ML) undoubtedly makes these technologies stand apart.
are essential enablers of digital transformation. The unique ability to distill all complex data into knowledge, along with judgment (AI) and mechanical rules (ML) undoubtedly makes these technologies stand apart.
In order to perform any specific task, AI and ML get to the atom of every job and get it done with comparative ease. In this way, rule-based work separates from knowledge-based work, which typically depends on critical thinking and decision-making skills. This process not only disrupts the current organizational working practices, but also improves the customer experience by reducing time, human resources required, and budget.
For instance: AI and ML, along with Data Science, create Inductive Logic
programming (ILPs) efficient for image and voice recognition. An ILP is the backbone of chatbots. Robotic Process Automation (RPA) is another specific case, which accurately illustrates a fundamental change in digital technology.
programming (ILPs) efficient for image and voice recognition. An ILP is the backbone of chatbots. Robotic Process Automation (RPA) is another specific case, which accurately illustrates a fundamental change in digital technology.
RPAs are software robots that first learn and then mimic and perform rule-based tasks. They easily interact with any computer application or system with 100% accuracy.
As AI and cognitive computing together erase out the demarcation between the digital and physical worlds, making cognitive systems think, observe, assimilate and learn like humans.
It properly understands the human inputs via Natural Language Processing (NLP) and replies using Dialog Management.
ML supports this continuous digital conversation. This technological breakthrough gifts us chatbots, which are of great significance in customer care across industries.
They can converse by text to text or text to voice, eliminating confusion
or a laid-back attitude of an incompetent customer care executive. It is not only customer care, AI and ML have revolutionized other important sections of business, like production and finance too.
or a laid-back attitude of an incompetent customer care executive. It is not only customer care, AI and ML have revolutionized other important sections of business, like production and finance too.
In order to build a quality chatbot, there are several bot builders available in the market. Although Chatbot4u is one of the archaic ecosystems for chatbots, there are few more quality substitutes, which I'll list in this article.
1. Api.ai (Dialogflow)
Api.ai is the most convenient way to get a chatbot-style AI personal
assistant. It allows developers to design artificially intelligent
models that they can train up with your custom functionality. Founded
in 2010, it gives innovative and engaging ways for users to interact
with the product. Although it does not allow a visual designer.
assistant. It allows developers to design artificially intelligent
models that they can train up with your custom functionality. Founded
in 2010, it gives innovative and engaging ways for users to interact
with the product. Although it does not allow a visual designer.
Benefits:
1. Several secured domains available.
2. Easy to build non-linear bots in no time
3. Integration with FB, Twilio and other platforms is simple.
2. Chatfuel
Chatfuel is a quality bot builder as it has a visual development environment. The main USP of Chatfuel is that it requires no code or tech
knowledge and anyone can build a simple bot for the business in just
a few hours.
knowledge and anyone can build a simple bot for the business in just
a few hours.
Benefits:
1. Less time taking process. One can build a simple bot quickly.
2. Deployment to FB Messenger is easy.
3. Outbound webhook support is excellent.
3. wit.ai
It is a free tool that anyone can employ. The platform has no visual
development environment, so the developer has to be comfortable
coding. Facebook acquired the platform, so it makes wit.ai, an
excellent choice for those who plan to develop chatbots for Facebook
Messenger. It supports about 50 different languages.
development environment, so the developer has to be comfortable
coding. Facebook acquired the platform, so it makes wit.ai, an
excellent choice for those who plan to develop chatbots for Facebook
Messenger. It supports about 50 different languages.
Benefits:
1. It supports around 50 languages.
2. Training of the engine goes around domain-specific use cases
3. Developer can train the model through a web interface.
4. IBM Watson conversation service
IBM Watson delivers a set of APIs and products like Virtual Agent,
Explorer, Analytics, and Knowledge Studio. The platform allows
developers to define the conversational logic for the bot. i.e logic
for what to say and when to say
Explorer, Analytics, and Knowledge Studio. The platform allows
developers to define the conversational logic for the bot. i.e logic
for what to say and when to say
Benefits:
1. Does not require much coding expertise.
2. Effective on smaller training datasets
5. ItsAlive
ItsAlive is a free platform used to make Facebook Messenger's
chatbots. It enables you to send periodic content each day, week, or
month, or manually send a one-time message to each chatbot
subscriber.
chatbots. It enables you to send periodic content each day, week, or
month, or manually send a one-time message to each chatbot
subscriber.
6. Rasa NLU
This platform consists of two units called NLU and Core. Rasa NLU supports HTTP API and Python for intent classification and entity extraction. The platform additionally includes all the features to create contextual, human-like conversations. Industries like insurance, banking, health, telecoms, travel, etc can use this platform.
In Conclusion:
Chatbots realistically pave the way forward for companies intending to optimize for superior customer service, marketing, and lead generation operations.
The unique combination of Artificial Intelligence (AI) and Natural Language Processing (NLP) has invariably produced some excellent results, and to get the desired results, one needs quality training datasets.